Agentic AI Engineer

Empiric; Göteborgs kommun; Hybrid; SEK 900,000 - 1,100,000; Full time

Benefits offered by this job

Hybrid work in Gothenburg (4 days on‑s

Job summary

Empiric in Gothenburg is seeking an Agentic AI Engineer to design, build and deploy agentic AI solutions on Azure, working across data science, cloud engineering and software delivery to take concepts into production. The initial term is 12 months, with a strong expectation that it will run well beyond that.

The role requires hands-on cloud engineering experience on Azure, strong CI/CD capabilities (Azure Pipelines, GitHub Actions) and expertise in Docker, Terraform and API development.

Qualifications

• Hands-on cloud engineering experience, primarily on Azure.
• Strong CI/CD experience with deployment strategies and git branching practices.
• Experience with microservices architecture and API development.

Skills

Cloud engineering

Azure

Data science

Machine learning

Mathematical statistics

Microservices

API development

Leadership

Regulatory governance

Vehicle data / telematics

Tools

Docker

Podman

Terraform

Azure Pipelines

GitHub Actions

Job description

We're recruiting an Agentic AI Engineer for a long-running contract with a client in Gothenburg. You'll design, build and deploy agentic AI solutions on Azure, working across data science, cloud engineering and software delivery to take them from concept into production. The initial term is 12 months, with a strong expectation that it will run well beyond that.

• Hands-on cloud engineering experience, primarily on Azure
• Solid experience with containerisation and infrastructure tooling (Docker, Podman, Terraform)
• Strong CI/CD experience (Azure Pipelines, GitHub Actions), including deployment strategies and git branching practices
• A strong grounding in data science, machine learning and AI, including mathematical statistics
• Experience with microservices architecture and API development

Nice to have

• Deep experience with LLMs, including retrieval, prompt engineering, evaluation, safety, and cost and performance tuning
• Experience delivering ML and AI in regulated environments with governance and audit requirements
• Domain experience with vehicle data, diagnostics, telematics, or quality and warranty analytics
• Leadership experience, such as owning ML products end to end, mentoring, or leading practitioner communities

Hybrid

• A hybrid setup in Gothenburg, with 4 days on-site